code: def daily_log_returns(data: pd.DataFrame) -> pd.DataFrame:
      """
      Returns DataFrame with daily log returns
  
      :math:`R_{\\log} = \\log\\left(1 + \\dfrac{\\text{price}_{t_i} - \\text{price}_{t_{i-1}}}
      {\\text{price}_{t_{i-1}}}\\right)`
  
      :param data: A dataframe of daily stock prices
  
      :return: A dataframe of daily log returns
      """
      # Type validations:
      type_validation(data=data)
      return (
          np.log(1 + daily_returns(data))
          .dropna(how="all")
          .astype(np.float64)
      )
  
file_path: FinQuant/finquant/returns.py
imports: from typing import Any
  import numpy
  import pandas
  from finquant.data_types import ARRAY_OR_SERIES, FLOAT, INT, NUMERIC, SERIES_OR_DATAFRAME
  from finquant.type_utilities import type_validation
label_desc: Use image node_id 4 for calling a global function with example usage: daily_log_returns(data) and returns: np